code: def test_burr_overflow():
      # this case leads to an overflow error if math.exp is used
      # in the definition of the burr pdf instead of np.exp
      # a direct implementation of the PDF as x**(-c-1) / (1+x**(-c))**(d+1)
      # also leads to an overflow error in the setup
      args = (1.89128135, 0.30195177)
      with suppress_warnings() as sup:
          # filter potential overflow warning
          sup.filter(RuntimeWarning)
          gen = FastGeneratorInversion(stats.burr(*args))
      u_error, _ = gen.evaluate_error(random_state=4326)
      assert u_error <= 1e-10
  
imports: import pytest
  import warnings
  import numpy
  from numpy.testing import assert_array_equal, assert_allclose, suppress_warnings
  from copy import deepcopy
  from scipy.stats.sampling import FastGeneratorInversion
  from scipy import stats
label_desc: Use image node_id 19 for calling a global function with example usage: test_burr_overflow() without return types